The paper reports a quantitative investigation into the nuances of gender perspectives of E-Learning utility across the social categorisations of Generation X, Y, and Z in the current phenomena of ...accelerated usage of e-learning in the emerging multi-generational undergraduate cohorts: using multi-generational undergraduate cohorts (N = 611) taking a mandatory online course in a Business School curricular. Using multi-group partial least-squares analysis, the study shows differences exist in the utility of e-learning within gender and Generations of X, Y, and Z. These differences may not be apparent when examined at only the gender level, which has led other researchers to conclude the gender gap is narrowing. However, we establish that within gender and across generations in a developing country context, the gender divide is not narrowing at the same pace as found in other developed countries. To accelerate the implementation of e-learning in traditional (face-to-face) undergraduate programmes globally, there is the need to contextualise Course Development, Learner Support, Assessment, and User Characteristics factors along with the different genders, and across generations to improve Results Demonstrability and Student Overall Satisfaction of utility of e-learning. In developing countries, there is a need to enhance Institutional factors to strengthen the drive to e-learning.
•E-learning in higher education continues to attract scholarly interest.•Understanding Utility essentials of multigenerational cohorts on e-learning is at an all-time High.•Perceived narrowing of the gender gap in e-learning is not obvious in a developing country case study.•Generations X, Y and Z cohorts across and within gender produce different Utility levels of e-learning.•Satisfaction differentials emanates from course design, delivery and learning environment.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Owing to the coronavirus outbreak, face-to-face educational activities have been curtailed and there has been a rapid switch to e-learning environments. It is a matter of critical importance; ...therefore, how ready teachers are for this transition. This study presents a snapshot of the readiness of Turkey's in-service teachers for teaching online. Some 555 teachers, from pre-school to high school, participated in the study. The results indicated a medium-level of e-learning readiness and a pressing need for the appropriate training. Teachers' readiness differed significantly according to gender, major, school-type, professional experience, teaching level, e-learning experience and Internet usage.
•COVID-19 entails e-learning, highlighting teachers' proficiency in e-learning.•Teachers have a mid-level of readiness, yet a high need for training in e-learning.•Males, computing-related majors, and private schools are readier for e-learning.•Teachers with high internet and e-learning experience are readier for e-learning.•Teaching level and experience affect e-learning readiness, but not consistently.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
This study aims to examine students' experience of augmented reality learning applications (AR.LRP). Uses and gratifications theory was proposed as a theoretical foundation of the current study's ...conceptual model. Four dimensions of UGT benefits were proposed as key antecedences of the students' experience with AR.LRP: personal interactive benefits, social interactive benefits, affective benefits, and cognitive benefits. The model was also extended by considering the role of telepresence. Further, technostress was proposed on the current study to moderate the relationship between the aspects of UGT and e-learning experience. A sample size of 500 undergraduate students from the four largest Universities in Saudi Arabia was used in the current study survey. The statistical results largely support the significant impact of personal interactive benefits, affective benefits, and cognitive benefits, and telepresence on student experience with AR.LRP. Technostress was also found to significantly moderate the relationship between UGT dimensions and student experience with AR.LRP. Further, results support a significant relationship between student experience with AR.LRP and students' learning performance. This study has contributed to the perspectives of researchers and practitioners by highlighting the most important aspects and characteristics that ensure a distinctive and positive students' experience of the drum with applications with AR.LRP.
•This study aims to examine students' experience of AR.LRP based on UGT as key antecedences.•The developed model considered the role of TELE in addition to TECHS as a moderator.•Results support the significant impact of PIB, AB, and CGB, and TELE on EXP.•TECHS significantly moderated the relationship between UGT dimensions and EXP.•Results also support a significant relationship between EXP and EP.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The sudden change in the learning process during the Covid-19 pandemic has brought schools at all levels to adopt e-learning. In this study, we analyze user acceptance of NUADU platform in private ...schools in Balikpapan, Indonesia. The extended Technology Acceptance Model is used as a reference model. The study results indicate that facilitating conditions have a significant effect on perceived usefulness. All core constructs of TAM have a significant effect except the relationship between perceived ease of use and attitude and perceived usefulness and behavior. Based on these findings, recommendations are then made to strengthen the acceptance of NUADU platform.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Prior studies on e-learning service quality were conducted mainly in developed countries; however, little effort has been made in emerging countries. This study examines the relationships among ...e-learning service quality attributes, overall e-learning service quality, e-learning student satisfaction, and e-learning student loyalty in the context of Vietnam, an emerging country. Survey data collected from 1232 college students were analyzed by means of exploratory factor analysis, confirmatory factor analysis, and structural equation modeling using SPSS 25 and SmartPLS 3.0. The results indicated that e-learning service quality was a second-order construct comprising of three factors, namely, e-learning system quality, e-learning instructor and course materials quality, and e-learning administrative and support service quality. The e-learning system quality was the most important dimension of overall e-learning service quality, followed by e-learning instructor and course materials quality, and e-learning administrative and support service quality. In addition, the overall e-learning service quality was positively related to e-learning student satisfaction, which in turn positively influences e-learning student loyalty. Also, overall e-learning service quality has a direct effect on e-learning student loyalty. Implications for colleges and universities are discussed.
Summary
Creating quality online content requires a great deal of effort from teachers. In addition to issues specific to the design and creation of the elements of a course, teachers must face ...technical hurdles so as to perform common tasks, such as deploying the same content on different e‐learning platforms and integrating content into external tools, or acquiring the ability to analyze tracking data generated during learner interactions. These problems principally arise owing to the very limited level of interoperability provided by content creation tools. In order to facilitate the creation of interoperable contents, the Digital Content Production Center at the Polytechnic University of Cartagena (Spain) has developed the UPCTforma tool, whose main architectural driver has been interoperability. More specifically, the tool takes advantage of the Learning Tools Interoperability and Caliper interoperability specifications to provide several types of quality regarding three key aspects of content production: tool interoperability, learning analytics, and motivation. In this paper, we provide a detailed description of the component‐based architecture proposed and present a validation of the requirements elicited through the use of a UPCTforma gamification activity created for a real project involving approximately 4000 students. One of the novel aspects of this architecture is the transformation of tracking data into “learning analysis models” that represent the information in the tracked learning activities at a higher level of ion. These models are used to provide activity‐specific learning analytics and motivation. Platform independency with respect to data analytics technologies, messaging systems, and communication protocols is achieved by using adapters.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
•The approach interprets the facial expressions to provide adaptive e-learning system.•The approach take the variances of learners’ emotional states into consideration.•The approach proposed a ...methodology to summarize the detected emotional states.•The approach uses fuzzy logic to create fuzzy learning flow adapted with each learner.•We introduce two real corpora to evaluate the performance of the proposed approach.
The integration of two or more intelligent systems, such as deep neural networks and fuzzy techniques, results in so-called hybrid intelligent systems. These have recently attracted considerable attention owing to their broad success in several complex real-world applications. An interesting example is the development of adaptive computer-based learning environments, in which learner responses to certain questions are considered so that the next level of the learning process may be determined. However, these methods fail to capture the behavior and emotional expressions of the learner during the learning process. Capturing these could make the learning flow more adaptive, and could allow the learning environment to redirect learners to different learning paths based on their capabilities and interaction levels. In this regard, the contribution of the present study is threefold. First, it proposes an approach for modeling an intelligent adaptive e-learning environment by considering the integration of the learner responses to questions and their emotional states. In the proposed approach, a loosely coupled integration between a convolutional neural network (CNN) and a fuzzy system is adopted. The CNN is used to detect a learner’s facial expressions, and outperforms other CNN models on the same training benchmark. The fuzzy system is used to determine the next learning level based on the extracted facial expression states from the CNN and several response factors by the learner. Second, the study introduces methods whereby a group of facial expressions is aggregated into a single representative. Third, it introduces corpora for evaluating the performance of the proposed approach. The corpora of 12 learners contain 72 learning activities and 1735 data points of distinct emotional states. The experimental results using these corpora demonstrate that the proposed approach provides adaptive learning flows that match the learning capabilities of all learners in a group. Moreover, the approach allows decision makers to monitor the learning performance for each learner.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
There has been little research on assessment of learning management systems (LMS) within educational organizations as both a web-based learning system for e-learning and as a supportive tool for ...blended learning environments. This study proposes a conceptual e-learning assessment model, hexagonal e-learning assessment model (HELAM) suggesting a multi-dimensional approach for LMS evaluation via six dimensions: (1) system quality, (2) service quality, (3) content quality, (4) learner perspective, (5) instructor attitudes, and (6) supportive issues. A survey instrument based on HELAM has been developed and applied to 84 learners. This sample consists of students at both undergraduate and graduate levels who are users of a web-based learning management system, U-Link, at Brunel University, UK. The survey instrument has been tested for content validity, reliability, and criterion-based predictive validity. The analytical results strongly support the appropriateness of the proposed model in evaluating LMSs through learners’ satisfaction. The explanatory factor analysis showed that each of the six dimensions of the proposed model had a significant effect on the learners’ perceived satisfaction. Findings of this research will be valuable for both academics and practitioners of e-learning systems.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
30.
Grit in the path to e-learning success Aparicio, Manuela; Bacao, Fernando; Oliveira, Tiago
Computers in human behavior,
January 2017, 2017-01-00, 20170101, Volume:
66
Journal Article
Peer reviewed
E-learning systems are emerging in many settings of our society. Schools, universities, and several other organizations use these systems. E-learning systems allow learning anytime and anywhere. This ...medium may seem to be the answer to all learning barriers, but the effect of non-cognitive skills on the success of e-learning systems is yet to be explored. Latest studies demonstrate that students with high grit levels, stamina in pursuing long term objectives, achieve better results in learning. In our study we propose a theoretical model studying grit as a determinant of e-learning systems success. The study was conducted on a sample of university students' sample, and a theoretical model was validated using structural equation modeling (SEM). Results indicate that grit has positive effects on satisfaction and in students' individual performance. The results help to improve e-learning strategies and to understand e-learning success, explained by students’ skills and systems characteristics.
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•Study about Grit impact on the use and satisfaction of e-learning systems.•Study supports Grit as a second-order construct of perseverance and consistency.•Non-cognitive student's characteristic determines information systems' success.•E-learning success determined by Grit, information, system, and service quality.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
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